Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2968
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.4 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qtd_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_products is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
recency_days is highly overall correlated with qtd_invoicesHigh correlation
avg_ticket is highly skewed (γ1 = 25.15696686) Skewed
frequency is highly skewed (γ1 = 24.87687084) Skewed
qtd_returns is highly skewed (γ1 = 21.9754032) Skewed
customer_id has unique values Unique
recency_days has 33 (1.1%) zeros Zeros
qtd_returns has 1481 (49.9%) zeros Zeros

Reproduction

Analysis started2025-03-24 17:08:07.731651
Analysis finished2025-03-24 17:08:36.708240
Duration28.98 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2968
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.377
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:36.883011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.35
Q113798.75
median15220.5
Q316768.5
95-th percentile17964.65
Maximum18287
Range5940
Interquartile range (IQR)2969.75

Descriptive statistics

Standard deviation1719.1445
Coefficient of variation (CV)0.11258036
Kurtosis-1.2061782
Mean15270.377
Median Absolute Deviation (MAD)1489
Skewness0.032193711
Sum45322479
Variance2955457.9
MonotonicityNot monotonic
2025-03-24T14:08:37.104062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
16956 1
 
< 0.1%
17010 1
 
< 0.1%
Other values (2958) 2958
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2953
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2693.4851
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:37.795218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.7325
Q1570.845
median1085.51
Q32306.905
95-th percentile7169.562
Maximum279138.02
Range279131.82
Interquartile range (IQR)1736.06

Descriptive statistics

Standard deviation10135.465
Coefficient of variation (CV)3.7629558
Kurtosis397.30132
Mean2693.4851
Median Absolute Deviation (MAD)670.84
Skewness17.635372
Sum7994263.7
Variance1.0272766 × 108
MonotonicityNot monotonic
2025-03-24T14:08:38.104290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
533.33 2
 
0.1%
734.94 2
 
0.1%
178.96 2
 
0.1%
1078.96 2
 
0.1%
598.2 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
889.93 2
 
0.1%
Other values (2943) 2948
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65039.62 1
< 0.1%

recency_days
Real number (ℝ)

High correlation  Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.309299
Minimum0
Maximum373
Zeros33
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:38.328340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.760922
Coefficient of variation (CV)1.2091707
Kurtosis2.7765172
Mean64.309299
Median Absolute Deviation (MAD)26
Skewness1.7980529
Sum190870
Variance6046.7611
MonotonicityNot monotonic
2025-03-24T14:08:38.560563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2218
74.7%
ValueCountFrequency (%)
0 33
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qtd_invoices
Real number (ℝ)

High correlation 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7243935
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:38.788613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8577599
Coefficient of variation (CV)1.5473709
Kurtosis190.78624
Mean5.7243935
Median Absolute Deviation (MAD)2
Skewness10.765555
Sum16990
Variance78.45991
MonotonicityNot monotonic
2025-03-24T14:08:39.026669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qtd_items
Real number (ℝ)

High correlation 

Distinct1670
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1582.1044
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:39.319734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile102.35
Q1296
median640
Q31399.5
95-th percentile4403.25
Maximum196844
Range196843
Interquartile range (IQR)1103.5

Descriptive statistics

Standard deviation5705.2914
Coefficient of variation (CV)3.6061408
Kurtosis516.7418
Mean1582.1044
Median Absolute Deviation (MAD)421
Skewness18.737654
Sum4695686
Variance32550350
MonotonicityNot monotonic
2025-03-24T14:08:39.581795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
88 9
 
0.3%
150 9
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
246 8
 
0.3%
288 8
 
0.3%
272 8
 
0.3%
1200 7
 
0.2%
114 7
 
0.2%
Other values (1660) 2885
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80263 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
63312 1
< 0.1%
58343 1
< 0.1%
57885 1
< 0.1%
50255 1
< 0.1%

qtd_products
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.76449
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:39.812845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7838
Range7837
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.93294
Coefficient of variation (CV)2.1987868
Kurtosis354.77884
Mean122.76449
Median Absolute Deviation (MAD)44
Skewness15.706135
Sum364365
Variance72863.79
MonotonicityNot monotonic
2025-03-24T14:08:40.051900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
1.4%
20 37
 
1.2%
29 35
 
1.2%
35 35
 
1.2%
19 34
 
1.1%
15 33
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
27 30
 
1.0%
25 30
 
1.0%
Other values (458) 2628
88.5%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 15
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 26
0.9%
10 28
0.9%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct1999
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.994208
Minimum2.15
Maximum4453.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:40.280951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.15
5-th percentile4.917
Q113.1175
median17.955
Q324.9825
95-th percentile90.053
Maximum4453.43
Range4451.28
Interquartile range (IQR)11.865

Descriptive statistics

Standard deviation119.53207
Coefficient of variation (CV)3.6228197
Kurtosis812.96474
Mean32.994208
Median Absolute Deviation (MAD)5.98
Skewness25.156967
Sum97926.81
Variance14287.915
MonotonicityNot monotonic
2025-03-24T14:08:40.511002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.49 7
 
0.2%
17.66 6
 
0.2%
16.39 6
 
0.2%
16.82 6
 
0.2%
19.06 6
 
0.2%
16.92 6
 
0.2%
18.38 5
 
0.2%
20.75 5
 
0.2%
10 5
 
0.2%
19.44 5
 
0.2%
Other values (1989) 2911
98.1%
ValueCountFrequency (%)
2.15 1
< 0.1%
2.43 1
< 0.1%
2.46 1
< 0.1%
2.51 1
< 0.1%
2.52 1
< 0.1%
2.65 1
< 0.1%
2.66 1
< 0.1%
2.71 1
< 0.1%
2.76 1
< 0.1%
2.77 1
< 0.1%
ValueCountFrequency (%)
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.99 1
< 0.1%
872.13 1
< 0.1%
841.02 1
< 0.1%
651.17 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-67.302133
Minimum-366
Maximum-1
Zeros0
Zeros (%)0.0%
Negative2968
Negative (%)100.0%
Memory size46.4 KiB
2025-03-24T14:08:40.733055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-366
5-th percentile-200.65
Q1-85.333333
median-48.267857
Q3-25.917308
95-th percentile-8
Maximum-1
Range365
Interquartile range (IQR)59.416026

Descriptive statistics

Standard deviation63.505358
Coefficient of variation (CV)-0.94358612
Kurtosis4.9080488
Mean-67.302133
Median Absolute Deviation (MAD)26.267857
Skewness-2.066084
Sum-199752.73
Variance4032.9306
MonotonicityNot monotonic
2025-03-24T14:08:40.966105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-14 25
 
0.8%
-4 22
 
0.7%
-70 21
 
0.7%
-7 20
 
0.7%
-35 19
 
0.6%
-49 18
 
0.6%
-21 17
 
0.6%
-46 17
 
0.6%
-11 17
 
0.6%
-42 16
 
0.5%
Other values (1248) 2776
93.5%
ValueCountFrequency (%)
-366 1
 
< 0.1%
-365 1
 
< 0.1%
-363 1
 
< 0.1%
-362 1
 
< 0.1%
-357 2
0.1%
-356 1
 
< 0.1%
-355 2
0.1%
-352 1
 
< 0.1%
-351 2
0.1%
-350 3
0.1%
ValueCountFrequency (%)
-1 16
0.5%
-1.5 1
 
< 0.1%
-2 13
0.4%
-2.5 1
 
< 0.1%
-2.601398601 1
 
< 0.1%
-3 15
0.5%
-3.321428571 1
 
< 0.1%
-3.330357143 1
 
< 0.1%
-3.5 2
 
0.1%
-4 22
0.7%

frequency
Real number (ℝ)

High correlation  Skewed 

Distinct1225
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11383237
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:41.199158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088935048
Q10.016339869
median0.025898352
Q30.049478583
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.033138713

Descriptive statistics

Standard deviation0.40822056
Coefficient of variation (CV)3.5861552
Kurtosis989.06632
Mean0.11383237
Median Absolute Deviation (MAD)0.012196886
Skewness24.876871
Sum337.85449
Variance0.16664402
MonotonicityNot monotonic
2025-03-24T14:08:41.421210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 18
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.02941176471 14
 
0.5%
0.03448275862 14
 
0.5%
0.02564102564 13
 
0.4%
0.01923076923 13
 
0.4%
Other values (1215) 2635
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtd_returns
Real number (ℝ)

Skewed  Zeros 

Distinct213
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.888477
Minimum0
Maximum9014
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:41.653261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100
Maximum9014
Range9014
Interquartile range (IQR)9

Descriptive statistics

Standard deviation282.86478
Coefficient of variation (CV)8.107685
Kurtosis596.20199
Mean34.888477
Median Absolute Deviation (MAD)1
Skewness21.975403
Sum103549
Variance80012.486
MonotonicityNot monotonic
2025-03-24T14:08:41.886316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
7 43
 
1.4%
8 43
 
1.4%
Other values (203) 705
23.8%
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation 

Distinct1978
Distinct (%)66.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean236.25289
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:42.125371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.2375
median172.29167
Q3281.54808
95-th percentile599.58
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)178.31058

Descriptive statistics

Standard deviation283.8932
Coefficient of variation (CV)1.2016496
Kurtosis102.78169
Mean236.25289
Median Absolute Deviation (MAD)83.041667
Skewness7.7018777
Sum701198.57
Variance80595.347
MonotonicityNot monotonic
2025-03-24T14:08:42.389427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
86 9
 
0.3%
73 9
 
0.3%
82 9
 
0.3%
60 8
 
0.3%
136 8
 
0.3%
75 8
 
0.3%
88 8
 
0.3%
71 7
 
0.2%
Other values (1968) 2881
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct906
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.489977
Minimum0.2
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-24T14:08:42.621482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile2
Q17.6666667
median13.6
Q322.144643
95-th percentile46
Maximum259
Range258.8
Interquartile range (IQR)14.477976

Descriptive statistics

Standard deviation15.460127
Coefficient of variation (CV)0.88394209
Kurtosis29.324685
Mean17.489977
Median Absolute Deviation (MAD)6.6
Skewness3.4364678
Sum51910.252
Variance239.01552
MonotonicityNot monotonic
2025-03-24T14:08:42.849532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 42
 
1.4%
9 41
 
1.4%
8 39
 
1.3%
16 39
 
1.3%
14 38
 
1.3%
17 38
 
1.3%
7 36
 
1.2%
11 36
 
1.2%
5 36
 
1.2%
15 35
 
1.2%
Other values (896) 2588
87.2%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.25 3
 
0.1%
0.3333333333 6
0.2%
0.4 1
 
< 0.1%
0.4090909091 1
 
< 0.1%
0.5 12
0.4%
0.5454545455 1
 
< 0.1%
0.5555555556 1
 
< 0.1%
0.5714285714 1
 
< 0.1%
0.6176470588 1
 
< 0.1%
ValueCountFrequency (%)
259 1
< 0.1%
177 1
< 0.1%
148 1
< 0.1%
127 1
< 0.1%
105 1
< 0.1%
104 1
< 0.1%
101 1
< 0.1%
98 1
< 0.1%
95.5 1
< 0.1%
94.33333333 1
< 0.1%

Interactions

2025-03-24T14:08:34.019349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:08.459981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:10.893532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:13.303078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:15.771634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.244162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:20.544685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:22.870208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.933054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.597555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:29.839412image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.848859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:34.201391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:08.708038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:11.071574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:13.516126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:15.959677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.437206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:20.730725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.038763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:25.118096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.785583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.015445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.026897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:34.380431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:08.921086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:11.259614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:13.722173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:16.138717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.621249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:20.915769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.204801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:25.307138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.970981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.176480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.198936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:34.558470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:09.134135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:11.460661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:13.928218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:16.333730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.816292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:21.110811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.376850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:25.494181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:28.159024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.348518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.375978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:34.723506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:09.330179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:11.648704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:14.117262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:16.508770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.989332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:21.315858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.538117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:25.671224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:28.326061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.510554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.547015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:34.910550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:09.554228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:11.854751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:14.344311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.019886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:19.184374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:21.532906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.726170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:25.866266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:28.522114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.693597image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.739057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.092594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:09.756274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:12.064796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:14.570364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.214929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:19.386421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:21.736951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:23.903203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:26.406397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:28.722152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:30.866636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:32.947106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.260628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:09.938317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:12.243835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:14.766406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.390972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:19.581463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:21.907991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.059857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:26.575427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:28.900199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.015668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:33.114145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.438670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:10.141363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:12.440884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:14.974454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.577011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:19.788512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:22.110036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.236901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:26.815967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:29.099237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.189710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:33.316190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.611709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:10.338407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:12.654932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:15.181501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.761054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:19.979558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:22.313083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.433940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.014998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:29.294279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.359748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:33.503234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.772743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:10.518448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:12.898985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:15.377545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:17.918088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:20.159596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:22.490123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.596978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.221357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:29.476323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.513783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:33.665268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:35.955795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:10.702489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:13.112034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:15.583593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:18.087126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:20.353637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:22.682166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:24.766017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:27.405399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:29.660362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:31.688821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-24T14:08:33.841310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-24T14:08:43.035575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtd_invoicesqtd_itemsqtd_productsqtd_returnsrecency_days
avg_basket_size1.0000.0780.1870.404-0.1230.0280.5740.1010.7290.3840.209-0.097
avg_recency_days0.0781.0000.123-0.131-0.0190.8810.2490.2580.2280.1650.398-0.109
avg_ticket0.1870.1231.000-0.618-0.1310.0910.2450.0600.166-0.3770.1890.049
avg_unique_basket_size0.404-0.131-0.6181.000-0.016-0.1220.106-0.1810.1480.515-0.0530.014
customer_id-0.123-0.019-0.131-0.0161.000-0.002-0.0770.026-0.0710.013-0.0640.001
frequency0.0280.8810.091-0.122-0.0021.0000.0910.0780.0810.0350.2350.017
gross_revenue0.5740.2490.2450.106-0.0770.0911.0000.7720.9250.7460.371-0.414
qtd_invoices0.1010.2580.060-0.1810.0260.0780.7721.0000.7180.6900.295-0.503
qtd_items0.7290.2280.1660.148-0.0710.0810.9250.7181.0000.7320.343-0.407
qtd_products0.3840.165-0.3770.5150.0130.0350.7460.6900.7321.0000.244-0.436
qtd_returns0.2090.3980.189-0.053-0.0640.2350.3710.2950.3430.2441.000-0.119
recency_days-0.097-0.1090.0490.0140.0010.017-0.414-0.503-0.407-0.436-0.1191.000

Missing values

2025-03-24T14:08:36.219847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-24T14:08:36.453900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.15-35.50000017.00000040.050.9705880.617647
1130473232.5956.09.01390.0171.018.90-27.2500000.02830235.0154.44444411.666667
2125836705.382.015.05028.0232.028.90-23.1875000.04032350.0335.2000007.600000
313748948.2595.05.0439.028.033.87-92.6666670.0179210.087.8000004.800000
415100876.00333.03.080.03.0292.00-8.6000000.07317122.026.6666670.333333
5152914623.3025.014.02102.0102.045.33-23.2000000.04011529.0150.1428574.357143
6146885630.877.021.03621.0327.017.22-18.3000000.057221399.0172.4285717.047619
7178095411.9116.012.02057.061.088.72-35.7000000.03352041.0171.4166673.833333
81531160767.900.091.038194.02379.025.54-4.1444440.243316474.0419.7142866.230769
9160982005.6387.07.0613.067.029.93-47.6666670.0243900.087.5714294.857143
customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
5626177271060.2515.01.0645.066.016.06-6.01.0000006.0645.00000066.000000
563617232421.522.02.0203.036.011.71-12.00.1538460.0101.50000015.000000
563717468137.0010.02.0116.05.027.40-4.00.4000000.058.0000002.500000
564813596697.045.02.0406.0166.04.20-7.00.2500000.0203.00000066.500000
5654148931237.859.02.0799.073.016.96-2.00.6666670.0399.50000036.000000
565812479473.2011.01.0382.030.015.77-4.01.00000034.0382.00000030.000000
567914126706.137.03.0508.015.047.08-3.00.75000050.0169.3333334.666667
5685135211092.391.03.0733.0435.02.51-4.50.3000000.0244.333333104.000000
569515060301.848.04.0262.0120.02.52-1.02.0000000.065.50000020.000000
571412558269.967.01.0196.011.024.54-6.01.000000196.0196.00000011.000000